Method for acoustic detection of shooter location

ABSTRACT

A method for acoustic detection of shooter location includes the following steps: receiving acoustic signals by a microphone array; detecting muzzle blast (MB) and shock wave (SW) signals through matched filter and cross correlation processes; transforming the detected MB and SW signals from time domain into frequency domain; beamforming the signals by means of the Delay and Sum method in frequency domain; estimating the direction of arrival (DOA) for the MB and SW signals by finding the azimuth and elevation which give the maximum power of the beamforming response; performing range estimation using the difference between the arrival time of the MB and SW signals together with the DOA estimations.

CROSS REFERENCE TO THE RELATED APPLICATIONS

This application is based upon and claims priority to Turkey PatentApplication No. 2017/21987, filed on Dec. 26, 2017, the entire contentsof which are incorporated herein by reference.

TECHNICAL FIELD

The present invention is particularly related to a beamforming-basedmethod for acoustic detection of shooter location. In the method of thepresent invention, the direction and range of the shooter are estimatedby means of signal processing methods based on beamforming using amicrophone array.

BACKGROUND

It is important to determine the location of a shooter for ensuring thesecurity of police stations, vehicles, convoys, borders, troops, societyand public and/or for sniper detection. The detection of shooterlocation is realized generally by the detection of acoustic signals suchas muzzle blast (MB) and shock wave (SW) associated with the projectile,and by the estimation of the direction and range of the aforementionedsignals by using various methods. In order to detect the acousticsignals and perform the aforementioned estimations, a single microphonearray or distributed microphone arrays are used. Acoustic signalsincident on the microphone array are processed using different methodsand estimations are obtained.

The publication No. U.S. Pat. No. 2,434,644, which is comprised in thestate of the art, direction of arrival (DOA) estimation according to thetime differences of arrival (TDOA) of the shock wave is described. Inthe publication No. U.S. Pat. No. 2,966,657, DOA is estimated bycollecting voltage polarizations from directional and non-directionalmicrophones by means of the cathode ray tube technology. In publicationsNo. U.S. Pat. No. 5,241,518 and No. U.S. Pat. No. 5,258,962 how thedirection of a supersonic projectile is determined by means of aplurality of microphones is described. Similarly, in the publication No.U.S. Pat. No. 6,669,477, a solution method is presented for the bullettrajectory estimation according to the TDOA of acoustic signals to sixmicrophones that are located discretely. In publication No. U.S. Pat.No. 6,563,763, a solution is proposed to improve the accuracy of bulletdirection estimations. In publications No. U.S. Pat. No. 7,190,633 andNo. U.S. Pat. No. 8,149,649, DOA is estimated according to the TDOA ofthe SW signal. The effects of the microphone location information on DOAestimation are analyzed, and a solution is proposed to reduce estimationerrors.

In the publication No. U.S. Pat. No. 5,544,129, DOA estimation is basedon the TDOA of acoustic signals on three microphones. In the publicationNo. U.S. Pat. No. 5,781,505, DOA estimation and localization areachieved using more than one array of microphones and optical sensors.In the publications No. U.S. Pat. Nos. 5,930,202 and 6,178,141, shootinglocation is estimated by using time of arrival (TOA) information with aplurality of microphone arrays. The publication No. U.S. Pat. No.6,965,312 explains shooter localization in a wireless communicationnetwork of multiple microphone arrays located on helmets of soldiers.Another solution based on the communication network among wearablemicrophone arrays is described in the publication No. U.S. Pat. No.7,266,045. In publications No. U.S. Pat. No. 7,126,877 and No. U.S. Pat.No. 7,408,840, target localization is performed by using the TDOA ofacoustic signals with at least five or seven microphones separated by adistance of at least 1 meter. U.S. Pat. Nos. 6,847,587, 7,139,222,7,433,266 and 7,586,812 can be shown as examples of publications inwhich the DOA estimation is accomplished by using distributed microphonearray networks.

U.S. Pat. No. 7,292,501 presents a system of two sensor units that areat least one meter apart and contain three accelerometers, where TDOA ofSW signals are used for target localization. In U.S. Pat. No. 7,495,998,acoustic sensor pairs are located with predetermined intervals accordingto the application. Shooter positioning is achieved by using thefrequency spectrum of the incoming acoustic signals, time delays,amplitude differences and periodicity information. In fixed or mobileplatforms and wearable system applications, usage of multi sensornetworks is proposed. The effect of increasing the number of the sensorson decreasing the estimation uncertainty is explained.

In the publication No. U.S. Pat. No. 7,583,808, microphones distributedwithin the task field, are first trained with acoustic patterns arrivingfrom different directions. Subsequently, a decision mechanism fordetermining the most probable location of the target through crosscorrelation of acoustic signals is described.

The sniper detection system proposed in U.S. Pat. No. 9,488,442 usescamera displays and radar systems together with a microphone array inorder to locate and track the shooter. Visual, acoustic and thermalinformation obtained from the shooting location are used for estimation.

In the publication No. U.S. Pat. No. 9,651,649, DOA estimation isperformed by using the TDOA of signals within a distributed network ofmicrophones. A system, where the network is partitioned into clusters ofat least four microphones, is described.

The approach generally used in the state of the art systems and methodsis based on the inference of the DOA of MB and SW signals from theirTDOA at array microphones. DOA estimation with time domain signalsbrings a lower limit to microphone spacing. In this approach, microphonespacing can be less than one meter only at very high samplingfrequencies. Even in this case, DOA estimation performance may not besatisfactory. Moreover, high sampling frequencies increase hardware andsoftware costs.

In most of the state of the art systems and methods, sensor unitsdistributed within the mission region are used. This situation, togetherwith signal processing, leads to network communication andsynchronization problems among sensor units. The required processingload for network communication and synchronization increases hardwareand software costs. On the other hand, transfer of raw data from sensorunits to a central processing unit causes delay, which reduces thevalidity and accuracy of estimations.

Due to the usage of optical and thermal systems together with acousticsensors, most of the detection and localization systems are expensive,complicated, and vulnerable to environmental conditions.

SUMMARY

The present invention introduces a novel approach for shooterlocalization. In the method of the present invention, acoustic signalsthat reach the microphones are transformed into frequency domain and DOAestimation for the signals is realized in frequency domain. Thesusceptibility of the frequency domain DOA estimation to microphoneaperture (the maximum distance between the most distant two microphonesin the array) and sampling frequency is much lower than that ofTDOA-based methods. This allows for lowering the array dimension to thehalf of the wavelength at 1 kHz (approximately 17 cm). Therefore, thepresent invention enables portable and wearable usage scenarios byadjusting microphone aperture according to application requirements.

The present invention avoids the necessity to use a distributed network,and the invention enables DOA estimation and localization of the shooterwith a system using only acoustic data. Therefore, problems that affectthe performance of the state of the art systems, such as delay,communication security, synchronization requirements and hardware costs,are prevented.

The aim of this invention is to introduce a beamforming-based method fordetection of shooter location. Direction and range of the shooterlocation is detected using a beamforming-based signal processing methodwith a microphone array.

Another aim of the present invention is to ensure the security of policestations, vehicles, convoys, borders, troops, society and public and/orfor sniper detection through shooter localization.

BRIEF DESCRIPTION OF THE DRAWINGS

A representative application of the method achieving the objectives ofthe present invention for shooter localization is illustrated in theattached figures in order to clarify the details of the invention. Thedetails of the description shall be considered by taking the wholedescription into account. In these figures;

FIG. 1 is a flowchart of a representative application of the method ofthe present invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

In the method of the present invention, acoustic signals are received byan array of acoustic receivers. Microphones, especially condenser typemicrophones; dynamic, capacitive, stripped, crystal, electret, andcarbon powdered microphones can be used as acoustic receivers withoutlimiting the invention. First, an MB or an SW is detected from thereceived acoustic signals. The received acoustic signals are crosscorrelated with model signals (the acoustic waveforms of the MB and SWsignals) by using a matched filter. The received signal is matched withthe MB or the SW model according to the result of the cross correlation.If the received acoustic signal is an MB or an SW signal, the detectedMB or SW signal is converted from time domain into frequency domain byusing Fast Fourier Transform (FFT).

Using the MB and SW signals received by the acoustic microphone array,beams are created for every possible direction in three dimensionalspace by Delay and Sum beamforming in frequency domain [B. D. Van Veen,K M Buckley, “Beamforming: A Versatile Approach to Spatial Filtering”,IEEE Acoustics, Speech and Signal Processing (ASSP) Magazine, 4-24(1988)]. DOA estimations for the MB and the SW signals are the maximumpower directions of the MB and the SW beams, respectively. The range(distance) that generates the arrival time difference of the MB and SWsignals is calculated. The location of the shooter is determined as aresult of the estimated DOA and range.

The processes in the preferred embodiment of the invention are asfollows:

Acoustic Receiver Array

The method of the invention comprises an array that consists of at leasttwo acoustic receivers that are appropriate for receiving acousticsignals such as sound waves. In a preferred embodiment of the inventionan acoustic receiver array that comprises condenser type microphones asacoustic receivers. The acoustic receiver aperture in the array isapproximately equal to the wavelength at 1 kHz. The acoustic receiveraperture is the distance between two furthest acoustic receivers in thearray.

The Detection of the Muzzle Blast (MB) and Shock Wave (SW) Signals

The acoustic signals received by the acoustic receiver array arecompared with the acoustic model waveforms of the MB and SW signals. Thereceived acoustic signal which is matched with one of the signal modelsis determined as an MB signal or an SW signal correspondingly. Theaforementioned comparison is made by taking the cross correlation of theMB model signal and the SW signal model with the received acousticsignal by using a matched filter.

Generation of the MB Signal Model

The MB signal model can preferably be formed as follows;

The modified Friedlander wave model is used for the MB signal model[Beck, S. D., Nakasone, H., Marr, K. W. (2011). “Variations in recordedacoustic gunshot waveforms generated by small firearms,” J. Acoust. Soc.Am. 129(4), 1748-1759.].

The positive phase part of the MB is calculated by the followingequation;

pp=Psp*(1−tp/T0p).*exp(b*tp/T0p)

Terminology:

-   -   pp=the positive phase part of the MB    -   Psp=the maximum pressure of the positive phase (in Pascals)    -   tp=the time vector for the positive phase (in seconds)    -   T0p=the duration of the positive phase (in seconds)    -   b=an exponential coefficient (unitless)    -   =multiplication    -   .*=element-wise multiplication

In addition to the positive phase part, the second part of the MBsignal, which is named as the negative phase, is calculated by thefollowing equation;

pn=−Pnp*(tn/T0n).*(1−tn/T0n).*exp(−4*tn/T0n)

Terminology:

-   -   pn=the negative phase part of the MB    -   Pnp=the maximum pressure of the negative phase (in Pascals)    -   tn=the time vector of the negative phase (in seconds)    -   T0n=the duration of the negative phase (in seconds)    -   *=multiplication    -   .*=element-wise multiplication

The MB signal model is obtained by concatenating the positive andnegative phase parts.

Generation of the SW Signal Model

The SW signal model can be preferably created as follows;

For the SW signal model, Whitham wave model [Stoughton, R. (1997).“Measurements of small-caliber ballistic shock waves in air,” J. Acoust.Soc. Am. 102(2), 781-787.] is used.

p_kernel_SD=Pmax*(1−2*(t/tmax))

Terminology:

-   -   p_kernel_S=SW signal model    -   t=time in seconds

Pmax=(0.53*P0*(M ²−1)^((1/8)) *d)/(b ^((3/4)) *l ^((1/4)))

-   -   -   P0=ambient pressure (in Pascals)        -   M=v/c Mach number (unitless)        -   v=speed of the bullet (meters/seconds)        -   c=speed of sound (meters/seconds)        -   d=caliber (in meters)        -   b=miss distance (in meters)        -   l=bullet length (in meters)

tmax=(1.82*M*b ^((1/4)) *d)/(c*(M ²−1)^((3/8)) *l ^((1/4))

-   -   -   M=v/c Mach number (unitless)        -   v=speed of the bullet (meters/seconds)        -   c=speed of sound (meters/seconds)        -   d=caliber (in meters)        -   b=miss distance (in meters)        -   l=bullet length (in meters)

Matched Filter and Cross Correlation Process

Separate cross correlations (matched filter) are carried out for thedetection of MB and SW signals. The cross correlation between thereceived signal (vector x of size Nx×1) and the theoretical signal model(vector y of size Ny×1) corresponding to the m-th delay is calculated asfollows:

Cxy(m)=Σ_(n)[x(n)*y(n+m)]

Terminology:

-   -   Cxy(m)=Cross correlation    -   x(n)=Received signal    -   y=Theoretical signal model    -   n=Time index    -   m=Time delay index

The time delay index (m) stands for the time difference in matching thereceived signal with the MB or SW signal model. The summation iscalculated over the time index n.

If a matching occurs as a result of the cross correlation, the receivedacoustic signal is detected either as an MB or as an SW signal.

Delay and Sum Beamforming

If an MB or an SW is detected, the received acoustic signal istransformed from time domain into frequency domain by means of the FastFourier transform (FFT). The aforementioned transformation process ispreferably performed as follows;

-   -   The acoustic signal of size (Nt×M), which is received by M        microphones at time index N is transformed into frequency domain        by FFT:

X(l,m)=Σ_(n) x(n,m)*exp(−i*2*π*n*l/Nt)

Terminology:

-   -   X(l, m)=FFT output of the signal of length Nt received by M        microphones    -   x(n, m)=The signal received by the microphones    -   i=(−1)^((1/2)) complex number    -   l=[0, Nfft−1] frequency index    -   m=[1, M] acoustic receiver channel    -   n=[1, Nt] time index    -   Nt=Number of samples in the received signal

The maximum amplitude in any channel (for example, at the 2ndchannel/column that belongs to a reference acoustic receiver) of theFourier coefficient matrix X with dimensions of ((Nfft/2+1)×M) is found.The frequency index (l0) and the frequency value (f0) corresponding tothe maximum amplitude is determined.

Subsequently, using the MB and SW signals received by the acousticmicrophone array, beams are created for every possible direction inthree dimensional space by Delay and Sum beamforming in frequency domain[B. D. Van Veen, K. M. Buckley, “Beamforming: A Versatile Approach toSpatial Filtering”, IEEE Acoustics, Speech and Signal Processing (ASSP)Magazine, 4-24 (1988)].

An MB or an SW signal is incident on each of the array microphones witha different delay. This delay is due to the spatial location differencesof the microphones in the acoustic receiver array. In the Delay and Summethod, for an acoustic signal incident on the microphone array, delaysare calculated in frequency domain for every possible DOA. These delaysare applied to the received acoustic signals, and then the signals aresummed up to form a beam for every possible DOA in three dimensionalspace. The abovementioned procedure is carried out for MB and SWsignals.

Azimuth (ψ) vector of size (359×1) and elevation (θ) vector of size(181×1) are created with a resolution of 1 degree for [0, 359] degreesand [−90, 90] degrees, respectively.

-   -   The beamforming response corresponding to the (azimuth ψ,        elevation θ) angle pair is calculated as:

r(ψ,θ)=Σ_(m) X(l0,m)*w(m)

Terminology:

-   -   X(l0, m)=Fourier coefficient at the frequency corresponding to        the maximum amplitude of channel m

w(m)=(1/M)*exp(−i*(2*π*f0/c)*Rs(1,m)*(cos(ψ−Rs(2,m))*cos(θ)*cos(Rs(3,m))+sin(θ)*sin(Rs(3,m)))

-   -   Rs(1, m)=Distance of m-th microphone to the center of the        receiver array    -   Rs(2, m)=Azimuth of m-th microphone with respect to the center        of the receiver array    -   Rs(3, m)=Elevation of m-th microphone with respect to the center        of the receiver array

DOA Estimation for MB and SW Signals

DOA estimations for the MB and the SW signals are the directions withthe maximum power for the MB and the SW beams, respectively.

The signal power in each direction of the beam is given by the followingequation:

b(ψ,θ)=|r(ψ,θ)|²

Terminology:

-   -   r(ψ,θ)=The beamforming response corresponding to the (azimuth        (ψ), elevation (θ) angle pair    -   b(ψ, θ)=Signal power in each direction    -   After beamforming for all azimuth and elevation directions, the        azimuth and the elevation of the incoming acoustic signal is        given by the maximum of the beamforming response:

(ψ₀,θ₀)=max_((ψ,θ))(b(ψ,θ))

Terminology:

ψ₀=The azimuth DOA with the maximum response

θ₀=The elevation DOA with the maximum response

Range Estimation

The range (distance) that generates the arrival time difference of theMB and SW signals is calculated. The location of the shooter isdetermined as a result of the estimated DOA and range.

The range is calculated by using the difference of velocities of MB andSW signals in air. Their arrival times at the acoustic receiver arrayare different. In a preferred embodiment of the invention, thedifference between the arrival times of MB and SW signals is taken asthe difference between the starting points of these signals, which aredetermined according to their cross correlations with the correspondingsignal models.

-   -   Using the (azimuth, elevation) DOA estimations for MB and SW        signals, which are denoted by (ψ_(SW), θ_(SW)) and (ψ_(MB),        θ_(MB)), unit vectors in these DOA directions are generated.

u _(SW)=[cos(ψ_(SW))*cos(θ_(SW)), sin(ψ_(SW))*cos(θ_(SW)),sin(θ_(SW))]^(T)

u _(MB)=[cos(ψ_(MB))*cos(θ_(MB)), sin(ψ_(MB))*cos(θ_(MB)),sin(θ_(MB))]^(T)

Terminology:

-   -   ψ_(SW)=The azimuth DOA estimation for the SW signal    -   θ_(SW)=The elevation DOA estimation for the SW signal    -   ψ_(MB)=The azimuth DOA estimation for the MB signal    -   θ_(MB)=The elevation DOA estimation for the MB signal    -   u_(SD)=Unit vector for the SW signal that has a DOA of (ψ_(SW),        θ_(SW))    -   u_(MB)=Unit vector for the MB signal that has a DOA of (ψ_(MB),        θ_(MB))    -   The cosine of the angle α between these two unit vectors is        obtained by means of scalar multiplication:

cos(α)=(u _(SW)(1)*u _(MB)(1))+(u _(SW)(2)*u _(MB)(2))+(u _(SW)(3)*u_(MB)(3))

-   -   Consequently, the firing range is calculated by using Δt value        that is the difference between the arrival times of the MB and        SW signals. The range value is calculated by

range=(Δt*c)/(1−cos(α)).

1. A method for an acoustic determination of a shooter location,comprising the following procedural steps: receiving acoustic signals bya microphone array; detecting a muzzle blast (MB) signal and a shockwave (SW) signal through a matched filter and cross correlationprocesses; transforming the MB signal and the SW signal from a timedomain into a frequency domain; beamforming the MB signal and the SWsignal by means of a Delay and Sum method in the frequency domain toobtain a MB beam and a SW beam; estimating a direction of arrival (DOA)for the MB signal and a direction of arrival (DOA) for the SW signal byfinding an azimuth and elevation, wherein the azimuth and elevationindicates the DOA of the MB signal having a maximum power of the MB beamand the DOA of the SW signal having a maximum power of the SW beam;performing a range estimation using a difference between arrival time ofthe MB signal and arrival time of the SW signal, the DOA for the MBsignal, and the DOA for the SW signal.
 2. The method according to claim1, further comprising the following steps: comparing each acousticsignal of the acoustic signals with an MB signal model and an SW signalmodel; in case a matching between the each acoustic signal and the MBsignal model or the SW signal model occurs, detecting the each acousticsignal as an MB signal or an SW signal accordingly.
 3. The methodaccording to claim 1, further comprising the following steps: performingthe cross correlation processes on each acoustic signal of the acousticsignals with an MB signal model and an SW signal model by using thematched filter; in case a matching between the each acoustic signal andthe MB signal model or the SW signal model occurs, detecting the eachacoustic signal as an MB signal or an SW signal accordingly.
 4. Themethod according to claim 2 wherein the MB signal model is a modifiedFriedlander wave model.
 5. The method according to claim 2 wherein theSW signal mode is a Whitham wave model.
 6. The method according to claim1, wherein the MB signal and the SW signal are transformed from the timedomain into the frequency domain through a Fast Fourier Transform. 7.The method according to claim 1, further comprising the following steps:calculating a delay of the DOA for MB the signal incident on themicrophones in the frequency domain; applying the delay to the MB signalincident on the microphones to obtain a delayed MB signal; summing thedelayed MB signal to form the MB beam through the Delay and Sum methodin three dimensional space.
 8. The method according to claim 1, furthercomprising the following steps: calculating a delay of the DOA for theSW signal incident on the microphones in the frequency domain; applyingthe delay to the SW signal incident on the microphones to obtain adelayed SW signal; summing the delayed SW signal to form the SW beamthrough the Delay and Sum method in three dimensional space.
 9. Themethod according to claim 1, wherein the DOA for the MB signal is adirection with the maximum power of the MB beam.
 10. The methodaccording to claim 1, wherein the DOA for the SW signal is a directionwith the maximum power of the SW beam.
 11. The method according to claim1, wherein in the step of performing the range estimation, a range iscalculated by using an MB unit vector in the DOA of the MB signal an SWunit vector in the DOA of the SW signal; the difference between thearrival time of the MB signal and the SW signal is multiplied by thespeed of sound to obtain a calculated product; and the calculatedproduct is divided by (1—the cosine of an angle between the MB unitvector and the SW unit vector).
 12. The method according to claim 3,wherein when calculating the difference between the arrival time of theMB signal and the arrival time of the SW signal, starting time of the MBsignal is given by an index of a maximum of a cross correlation betweenthe MB signal and a corresponding theoretical MB signal model, andstarting time of the SW signal is given by an index of a maximum of across correlation between the SW signal and a corresponding theoreticalSW signal model.
 13. The method according to claim 2, further comprisingthe following steps: performing the cross correlation processes on eachacoustic signal of the acoustic signals with an MB signal model and anSW signal model by using the matched filter; in case a matching betweenthe each acoustic signal and the MB signal model or the SW signal modeloccurs, detecting the each acoustic signal as an MB signal or an SWsignal accordingly.
 14. The method according to claim 2, wherein the MBsignal and the SW signal are transformed from the time domain into thefrequency domain through a Fast Fourier Transform.
 15. The methodaccording to claim 2, further comprising the following steps:calculating a delay of the DOA for the MB signal incident on themicrophones in the frequency domain; applying the delay to the MB signalincident on the microphones to obtain a delayed MB signal; summing thedelayed MB signal to form the MB beam through the Delay and Sum methodin three dimensional space.
 16. The method according to claim 2, furthercomprising the following steps: calculating a delay of the DOA for theSW signal incident on the microphones in the frequency domain; applyingthe delay to the SW signal incident on the microphones to obtain adelayed SW signal; summing the delayed SW signal to form the SW beamthrough the Delay and Sum method in three dimensional space.
 17. Themethod according to claim 2, wherein the DOA for the MB signal is adirection with the maximum power of the MB beam.
 18. The methodaccording to claim 2, wherein the DOA for the SW signal is a directionwith the maximum power of the SW beam.
 19. The method according to claim2, wherein in the step of performing the range estimation, a range iscalculated by using an MB unit vector an SW unit vector in the DOA ofthe MB signal and the SW signal; the difference between the arrival timeof the MB signal and the SW signal is multiplied by the speed of soundto obtain a calculated product; and the calculated product is divided by(1—the cosine of an angle between the MB unit vector and the SW unitvector).
 20. The method according to claim 3, wherein the MB signalmodel is a modified Friedlander wave model.